Filtered By:
Source: Sensors
Condition: Spinal Cord Injury
Education: Learning

This page shows you your search results in order of date.

Order by Relevance | Date

Total 2 results found since Jan 2013.

Sensors, Vol. 21, Pages 2084: Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges
Astaras Recent advances in the field of neural rehabilitation, facilitated through technological innovation and improved neurophysiological knowledge of impaired motor control, have opened up new research directions. Such advances increase the relevance of existing interventions, as well as allow novel methodologies and technological synergies. New approaches attempt to partially overcome long-term disability caused by spinal cord injury, using either invasive bridging technologies or noninvasive human–machine interfaces. Muscular dystrophies benefit from electromyography and novel sensors that shed light on under...
Source: Sensors - March 16, 2021 Category: Biotechnology Authors: Nizamis Athanasiou Almpani Dimitrousis Astaras Tags: Review Source Type: research

Sensors, Vol. 19, Pages 210: Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals
Jörg Conradt Non-invasive, electroencephalography (EEG)-based brain-computer interfaces (BCIs) on motor imagery movements translate the subject’s motor intention into control signals through classifying the EEG patterns caused by different imagination tasks, e.g., hand movements. This type of BCI has been widely studied and used as an alternative mode of communication and environmental control for disabled patients, such as those suffering from a brainstem stroke or a spinal cord injury (SCI). Notwithstanding the success of traditional machine learning methods in classifying EEG signals, these methods still rely ...
Source: Sensors - January 8, 2019 Category: Biotechnology Authors: Zied Tayeb Juri Fedjaev Nejla Ghaboosi Christoph Richter Lukas Everding Xingwei Qu Yingyu Wu Gordon Cheng J örg Conradt Tags: Article Source Type: research